--- permalink: python/violin/ description: How to make violin plots in Python with Plotly. name: Violin Plots has_thumbnail: true thumbnail: thumbnail/violin.jpg layout: user-guide language: python title: Violin Plots | Plotly display_as: statistical has_thumbnail: true page_type: u-guide order: 12 --- {% raw %}
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import plotly
plotly.__version__
import plotly
import plotly.offline as off
import pandas as pd
off.init_notebook_mode()
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/violin_data.csv")
fig = {
"data": [{
"type": 'violin',
"y": df['total_bill'],
"box": {
"visible": True
},
"line": {
"color": 'black'
},
"meanline": {
"visible": True
},
"fillcolor": '#8dd3c7',
"opacity": 0.6,
"x0": 'Total Bill'
}],
"layout" : {
"title": "",
"yaxis": {
"zeroline": False,
}
}
}
plotly.offline.iplot(fig, validate = False)
import plotly
import plotly.offline as off
from plotly.graph_objs import Layout, Figure
import pandas as pd
off.init_notebook_mode()
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/violin_data.csv")
data = []
for i in range(0,len(pd.unique(df['day']))):
trace = {
"type": 'violin',
"x": df['day'][df['day'] == pd.unique(df['day'])[i]],
"y": df['total_bill'][df['day'] == pd.unique(df['day'])[i]],
"name": pd.unique(df['day'])[i],
"box": {
"visible": True
},
"meanline": {
"visible": True
}
}
data.append(trace)
fig = {
"data": data,
"layout" : {
"title": "",
"yaxis": {
"zeroline": False,
}
}
}
plotly.offline.iplot(fig, validate = False)
import plotly
import plotly.offline as off
import pandas as pd
off.init_notebook_mode()
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/violin_data.csv")
fig = {
"data": [
{
"type": 'violin',
"x": df['day'] [ df['sex'] == 'Male' ],
"y": df['total_bill'] [ df['sex'] == 'Male' ],
"legendgroup": 'M',
"scalegroup": 'M',
"name": 'M',
"box": {
"visible": True
},
"meanline": {
"visible": True
},
"line": {
"color": 'blue'
}
},
{
"type": 'violin',
"x": df['day'] [ df['sex'] == 'Female' ],
"y": df['total_bill'] [ df['sex'] == 'Female' ],
"legendgroup": 'F',
"scalegroup": 'F',
"name": 'F',
"box": {
"visible": True
},
"meanline": {
"visible": True
},
"line": {
"color": 'pink'
}
}
],
"layout" : {
"yaxis": {
"zeroline": False,
},
"violinmode": "group"
}
}
plotly.offline.iplot(fig, validate = False)
import plotly
import plotly.offline as off
import pandas as pd
off.init_notebook_mode()
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/violin_data.csv")
fig = {
"data": [
{
"type": 'violin',
"x": df['day'] [ df['smoker'] == 'Yes' ],
"y": df['total_bill'] [ df['smoker'] == 'Yes' ],
"legendgroup": 'Yes',
"scalegroup": 'Yes',
"name": 'Yes',
"side": 'negative',
"box": {
"visible": True
},
"meanline": {
"visible": True
},
"line": {
"color": 'blue'
}
},
{
"type": 'violin',
"x": df['day'] [ df['smoker'] == 'No' ],
"y": df['total_bill'] [ df['smoker'] == 'No' ],
"legendgroup": 'No',
"scalegroup": 'No',
"name": 'No',
"side": 'positive',
"box": {
"visible": True
},
"meanline": {
"visible": True
},
"line": {
"color": 'green'
}
}
],
"layout" : {
"yaxis": {
"zeroline": False,
},
"violingap": 0,
"violinmode": "overlay"
}
}
plotly.offline.iplot(fig, validate = False)
import plotly
import plotly.offline as off
import pandas as pd
off.init_notebook_mode()
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/violin_data.csv")
pointposMale = [-0.9,-1.1,-0.6,-0.3]
pointposFemale = [0.45,0.55,1,0.4]
showLegend = [True,False,False,False]
data = []
for i in range(0,len(pd.unique(df['day']))):
male = {
"type": 'violin',
"x": df['day'][ (df['sex'] == 'Male') & (df['day'] == pd.unique(df['day'])[i]) ],
"y": df['total_bill'][ (df['sex'] == 'Male') & (df['day'] == pd.unique(df['day'])[i]) ],
"legendgroup": 'M',
"scalegroup": 'M',
"name": 'M',
"side": 'negative',
"box": {
"visible": True
},
"points": 'all',
"pointpos": pointposMale[i],
"jitter": 0,
"scalemode": 'count',
"meanline": {
"visible": True
},
"line": {
"color": '#8dd3c7'
},
"marker": {
"line": {
"width": 2,
"color": '#8dd3c7'
}
},
"span": [
0
],
"showlegend": showLegend[i]
}
data.append(male)
female = {
"type": 'violin',
"x": df['day'] [ (df['sex'] == 'Female') & (df['day'] == pd.unique(df['day'])[i]) ],
"y": df['total_bill'] [ (df['sex'] == 'Female') & (df['day'] == pd.unique(df['day'])[i]) ],
"legendgroup": 'F',
"scalegroup": 'F',
"name": 'F',
"side": 'positive',
"box": {
"visible": True
},
"points": 'all',
"pointpos": pointposFemale[i],
"jitter": 0,
"scalemode": 'count',
"meanline": {
"visible": True
},
"line": {
"color": '#bebada'
},
"marker": {
"line": {
"width": 2,
"color": '#bebada'
}
},
"span": [
0
],
"showlegend": showLegend[i]
}
data.append(female)
fig = {
"data": data,
"layout" : {
"title": "Total bill distribution<br><i>scaled by number of bills per gender",
"yaxis": {
"zeroline": False,
},
"violingap": 0,
"violingroupgap": 0,
"violinmode": "overlay"
}
}
plotly.offline.iplot(fig, validate = False)
See https://plot.ly/python/reference/ for more information and chart attribute options!